Ep 78: Jordan Schneider, Host of China Talk, on AI Race, Key Policy Decisions & Unpacking Geopolitical Chip Tension

This week on Unsupervised Learning, Jacob Effron is joined by Jordan Schneider, host of China Talk, who challenges widespread assumptions about US-China AI competition. China's AI development is driven by private capital and market competition—not central government planning—with companies like DeepSeek, Alibaba, and ByteDance operating more like Silicon Valley startups than state projects. The critical bottleneck is compute: the West maintains a 10-15x advantage in advanced chips, and US export controls implemented one month before ChatGPT created a structural edge favoring America for years. Chinese companies aggressively open-source models from strategic necessity—they couldn't establish a quality gap justifying paid access like OpenAI. Jordan explains why the "Goldilocks strategy" of controlled chip dependency fails, why expert consensus opposes selling advanced semiconductors to China despite Nvidia's lobbying, and how Taiwan's invasion risk is driven more by domestic politics than AGI scenarios. China's real advantage may emerge in robotics manufacturing at scale, where they're already deploying while the US debates strategy.

• 0:00Speaker 00

  Could you just walk us through what's happened in the Chinese AI ecosystem?

• 0:03Speaker 01

  The Chinese government, I think, post-reform era, hardware over software.

• 0:07Speaker 00

  What's the general attitude of like Chinese founders and builders?

• 0:10Speaker 01

  The main focus is a kind of competitive pressure, one, to stay alive. China's never stopped, right?

• 0:18Speaker 00

  I remember this whole debate of like, can even make a good model, given the type of censorship you'd have to do.

• 0:23Speaker 01

  If you can figure out how to make a model not racist, you can figure out how to have it not say politically controversial things.

• 0:28Speaker 00

  What role is the Chinese government playing?

• 0:30Speaker 01

  The story of the Chinese government with respect to AI has been.

• 0:35Speaker 00

  Jordan Schneider is one of the preeminent thinkers around China, host of the popular blog and podcast China Talk. I'm Jacob Effron, and today on Supervised Learning, I sat down with Jordan, who's also been a close friend for about 15 years. We had a really interesting discussion. We hit on the Chinese AI ecosystem overall, some of the key players and trends and what's going on. We talked about the Chinese government and their attitude toward that ecosystem and how they're supporting it. And we talked about US policies toward China. We got Jordan's take on a bunch of the key questions around chips being debated right now. And like any good conversation with Jordan, we had about 15 tangents in between. Overall, a really fun episode. I think folks will really enjoy this. Without further ado, here's Jordan. Jordan, thanks so much for coming on the podcast.

• 1:10Speaker 01

  What a pleasure, Jacob. Long time coming. 15 years in the making.

• 1:14Speaker 00

  I know. Who would have thought, you know, six, seven years ago, when I went into venture and you started like this China newsletter, that we would have a joint podcast?

• 1:22Speaker 01

  I did.

• 1:22Speaker 00

  You saw this day?

• 1:23Speaker 01

  Of course. I've been waiting for it ever since we revived a failing college politics magazine together.

• 1:30Speaker 00

  That is true. Still a career highlight.

• 1:33Speaker 01

  Indeed.

• 1:34Speaker 00

  Maybe we can get the Yale Politics to cover this episode.

• 1:36Speaker 01

  You think they'll sponsor us?

• 1:37Speaker 00

  Yeah, maybe a little ad or something.

• 1:39Speaker 01

  Sure. Hi, guys.

• 1:41Speaker 00

  Well, very much looking forward to having you on. We have not done a bunch of China stuff on this podcast to date, and so I think you will be our resident expert for our audience. I'm going to kick things off in like the most Broadway possible. Could you just walk us through what's happened in the Chinese AI ecosystem, pre-chat GPT and post-chat GPT?

• 1:58Speaker 01

  Pre-chat GPT, we had a Chinese AI ecosystem, which was doing AI not in the sort of like LLM scaling laws paradigm. There was a lot of sort of vision stuff, which was world-class. And you know, the inklings of beginnings on robotics models, but the sort of, you know, scaling is all you need transformer architecture paradigm, which brought us OpenAI and Anthropic and ChatGPT and the world that we've been living in for the past three years was not something that really anyone in a Chinese technology company was investing a lot in.

• 2:40Speaker 01

  So it was a real wake up call for the Chinese technology ecosystem with sort of lots of hand wringing, but also kind of energy and excitement and funding that this sort of broader technology ecosystem, which was really desiccated in the wake of COVID and the tech clash and crackdown that you saw really from like 2018, 2019, all the way through fall of 2022. On the one hand, was very freaked out that like America had this incredible cool thing that China didn't. But also there was enough capital, talent,

• 3:21Speaker 01

  like compute, energy in order for lots of experiments to be started. So over the course of 2023 and 2024, you had a number of labs spin up. I think probably like 12 or 15, if we really want to like expand the bubble of like who was credible.

• 3:42Speaker 00

  And how much of a coordinated effort was that like top down versus like, hey, there's just a lot of talent?

• 3:47Speaker 01

  So the interesting thing about the Chinese government and Xi in particular, but the Chinese government, I think really over, you know, post reform era, hardware over software. So software innovation, software companies were not conceived by the central government as like contributing to national power and national greatness. And the sort of reason that you had the tech clash and all this drama with Ant Financial and DD getting smacked down and whatnot was because at the end of the day, the Chinese government did not see software led companies as like really doing all that much.

• 4:25Speaker 01

  Fundamental to make China flourish in the way that the party envisioned it doing so.

• 4:32Speaker 00

  Well, it seems like they thought it was actually bad for society.

• 4:34Speaker 01

  Yeah, that, yeah, that, that these, these great engineers working on algorithms and models are wasting their time rotting our children's brains when they could be, you know, designing cars and weapon systems and what have you. So the 2023 sort of expansion was a fascinating one because it was almost entirely sort of private money driven, where you had these VCs who like, were really just sad. There are all these like, like tearjerker articles about, we have nothing to invest in. We can't raise our next round. It was like, okay, we have a new story to tell. And because the Chinese government very early on banned

• 5:15Speaker 01

  Western closed models from getting deployed within China, you have this protected market, which is a dynamic we've seen in many, and like many other sort of big corporate stories over the past 30 years in China. So I would say that there has been an enormous amount of Chinese subsidization and support on the hardware side, trying to build a kind of separate and resilient ecosystem away from the sort of like TSMC and, you know, Tokyo Electron and ASMLs of the world into something that China wouldn't be vulnerable to from an export controls perspective to the tunes of

• 5:53Speaker 01

  hundreds and hundreds of billions of dollars over the past 15 years. But on the sort of software side of things, like very little. And it's, from a financial perspective, it started to be

• 6:08Speaker 01

  on the margins, but like DeepSeek is, DeepSeek and Alibaba, Qwen and Minimax and Kimi are not, you know, Chinese government innovation stories. They are Chinese engineering, Chinese private capital, Chinese like big software companies that got hated on for the past five years stories, just being able to do their thing and ultimately deliver models. Which are, you know, competing globally.

• 6:37Speaker 00

  Were these efforts like venture funded? Because obviously you had these big companies that like did, you know, you know, that produced these models. And then my impression of DeepSeek was it was like some hedge fund that like started doing these things. What is the story behind a lot of these like major Chinese players that we hear about?

• 6:51Speaker 01

  So it's all of the above. DeepSeek is this weird exception of this guy who ran a hedge fund who just thought models were cool. You know, he was sort of like Zuckerberg and he just like bought a lot of Nvidia chips before they became impossible to buy. And he had a team that was sort of working on this. And then they ended up, you know, going from spending time making like high frequency trading models to to large language models. Alibaba, China's biggest cloud provider, China's biggest owns China, the largest kind of e-commerce platform in China, also a big payments business, a big sort of like finance business as well on the side of it.

• 7:32Speaker 01

  They were working, you know, had had enough computer science talent, brought in a lot more. Other big companies like ByteDance, which, you know, you got, you guys know what TikTok is. You know, had talent and capital and compute. There are a handful of smaller models which did raise VC funding. I think having, there were a handful of folks who had a pedigree from, you know, having worked in in Western labs, primarily there's a big kind of US-China knowledge interaction transfer which we can get into. But yeah, you had, you saw raises of, you know, not like OpenAI and Anthropic raises, but, you know, eight figures, like low nine figures

• 8:16Speaker 01

  to try to spin up something with like business model TBD, but like, let's just go train some stuff and we'll figure it out on the backside.

• 8:22Speaker 00

  Sounds familiar. I mean, who like, obviously in the US, the version of these has been folks that were in the big labs, you know, a lot out of like DeepMind or, you know, or Meta or OpenAI or Anthropic and they spun out and they start these new labs. Like the set of people that are at the forefront of the model development ecosystem in China, a lot of them have Western experience? Is it just like, hey, once, you know, it became clear to scale transformers, like there's certainly plenty of great engineers over there. Been messing with this stuff like who are a lot of these people?

• 8:47Speaker 01

  Both. So we have folks with PhDs at Carnegie Mellon, folks who've spent time in Microsoft and Google. DeepSeek is an interesting exception where the sort of lore is that his English wasn't even good enough to like get into the top grad schools in China. So like, yeah, he wasn't about to move to the to the US and sort of made a point of only hiring domestic talent because he thought it was kind of underpriced in the marketplace. But you know, if you go through the background of a lot of these top researchers, like the way they establish their credentials, both to the large kind of established tech firms that want to hire them as well as the funders who they need to raise money

• 9:31Speaker 01

  from is by having some sort of kind of Western big tech or Western academic credential. Though this is changing and I think sort of one of the remarkable things of like, you know, you've had a lot of young researchers on your podcast is this isn't necessarily a field where you need to have spent 20 years in it to be on the frontier. This was one of the

• 9:55Speaker 01

  the open questions that some people, but not China Talk readers had over the course of the past five years is like, can Chinese engineers do it? Are they creative enough? Are they lateral thinking enough? And it's like, yeah, they can. It's a big country. They got a lot of really smart folks. And by the way, you know, if you look at a lot of these Western labs, like a third of the last names are Chinese and those Chinese of that third, I would say two thirds or three quarters of them grew up in mainland China. So there's just an enormous amount of cultural exchange, intellectual exchange, academic exchange, which is happening before and continues continues to happen even or despite all of the kind of geopolitical tension that's being you know, spun up because of all of this.

• 10:36Speaker 00

  That like research collaboration, do you expect that to continue? What are what are what's in the tea leaves there?

• 10:42Speaker 01

  We'll see, man. I'm going to NERUPS next week, which is in San Diego. This year is the first year they've had to spin up a second off-site one in Mexico, basically because Chinese researchers struggled to get visas to the most important AI research conference in the world. And that, I think, is like emblematic of a lot of the sort of larger challenges that these two ecosystems are, you know, have today and will continue to have to like play nice. I mean, we are not in a sort of like perfect, perfect, open, free market. This is a, this is a dual-use technology. This is the, you know, the story of the decade when it comes to economic growth.

• 11:23Speaker 00

  I guess, you know, going back to your timeline, it felt like, you know, with Deep Seek and then afterwards, there's been this collective movement in China of open sourcing models. What's up with that?

• 11:33Speaker 01

  It's a good question, because as, as you can tell better, you know, as you know better than I do, it's hard to make money when you're not selling a thing, right? So I think from the beginning, it was a sort of market adoption play and a bit of a race to the bottom play where like if there was a really good model that was open source and free, it would be really hard to sell a closed model, which was not all that much better. And in the US, you did, over the past three years, really have a considerable gap where if you wanted to have access to the best capabilities, you could pay for it.

• 12:12Speaker 00

  Yeah, I mean, Meta tried the strategy and then backed out, right? It just didn't work.

• 12:15Speaker 01

  I think a few things happened. So like, the technology ended up working out that you could get really good, pretty close stuff without having to spend tens of, you know, billions of dollars on training runs, which is something that made it easier for the Chinese players to, to take this, to be able to sell stuff which was like pretty good and still, and still usable in this paradigm. You know, all the firms are trying to make money. Like, we had the one year of fun research, let's just, let's just do stuff. And now there's starting to be more of a crunch. Our, our 15 AI labs that we started with are now down to like really five. Five or six and most of them are sort of either like deep seek is is an exception,

• 12:58Speaker 01

  but most of them are sort of like aligned with either Tencent or Alibaba. And then the sort of the the applications and use cases are much more straightforward. Like, yeah, if you are Amazon, you want to have a model. So ChatGPT doesn't take over like the whole buying ecosystem. That's sort of the same thing from the Alibaba perspective. And OpenAI has not really been born in China. It's still like a few small players who are futzing around and making pretty good models and a handful of giant companies who can pay for this because like they have other businesses which make enormous amounts of money and spin enough spin up enough cash for them to, you know, stay relatively close to the frontier.

• 13:38Speaker 00

  Right, but I mean, to your earlier point, it seems like to the extent that similar use cases to the US will exist in China and the fact that these closed source models are banned in China, there feels like a large market. Like, do you expect the Chinese L market to kind of shake out similarly to the way the US one has?

• 13:52Speaker 01

  That's a really good question. I mean, I think it hasn't because we don't have AI labs that are strong enough to stand on their own. And I think that is sort of like, this comes back to like a fundamental difference between the sort of broader Western ecosystem and the Chinese one is there's just more VC money sloshing around in order to scale up an OpenAI or an Anthropic to be able to compete with the likes of a with the likes of a Google, right? And what we've now seen in China is like, you know, we'll see, maybe some of these smaller labs will try to go public and raise a lot of money. But the sort of relative, the relative independence that, I mean, not really Anthropic

• 14:35Speaker 01

  because they're kind of like, you know, beholden to a lot of these other players. But but OpenAI has been able to develop over the past three years is not something that's happened to any of the sort of players who've entered over the past three years in China.

• 14:48Speaker 00

  Right. I mean, while the Chinese government just, you know, sit on the sidelines and be like, hey, let this develop as it develops. Like, I imagine there's a huge incentive to concentrate compute, concentrate talent, like really get something state of the art or what's their attitude toward the? Stuff Ben.

• 15:02Speaker 01

  Yes and no. I mean, I think it's working pretty good. If you're, if you're, if you're on the Chinese side like, look, pre-training is nice. But by the way, the Chinese firms can still access compute abroad. And the best, you know, and sort of use the best Nvidia chips. And we have this famous Oracle, basically powering all of ByteDance in America, which is maybe the, the, the story that's gotten the most headlines. But, but the sort of, the compute constraint is as much one of capital for now as it is, as it is like a coordination problem. And, you know, there's lots of downsides to like,

• 15:42Speaker 01

  putting your thumb on the scale and saying you're the, you're the lab that we want to have win it all. And, and really what we've seen over the course of, how the Chinese government has sort of shepherded the growth of other emerging technologies and industries is they're fine to have companies fight it out for a while. Right? Like BYD was not anointed. Huawei was not anointed. They had to like, battle for a deck, you know, I mean, in Huawei's case, like multiple decades before they sort of rose to national champion status. So we're still in the early innings on that and that phase. And I don't think the technology

• 16:20Speaker 01

  today is quite the sort of, you know, AI 2027, like one, one, you know, one run to rule them all. And if you don't get it, you're going to be lost forever. It's a much more dynamic ecosystem. It's a repeated game. We're still figuring out the business models even. Much less like whether or not AGI will be achieved. Once I collect enough chips in a basement.

• 16:43Speaker 00

  What role is the Chinese government playing? You alluded to like, obviously very focused on the hardware side, super involved in chips and reducing dependencies there. Anything else they're kind of like focused on?

• 16:52Speaker 01

  People probably heard of America's AI action plan, like China had a version of it. It's all kind of like, fine, not super dramatic. Yeah, we're gonna do more AI in education. We're gonna do more AI in healthcare. We think open models are cool.

• 17:04Speaker 00

  They also have like relatively meaningless platitudes in their government docs.

• 17:08Speaker 01

  Oh, yeah. 70% adoption in all companies by 2035. Like, okay, cool. That seems, that's, that seems like a nice idea. Um, you know, one of the sort of like risk vectors that people were talking about was that the Chinese government would be really scared of what these models would produce and then kind of like crack down on, uh, you know, folks access to it because they're worried they'd be making-

• 17:34Speaker 00

  I remember this whole debate of like, if you could even make a good model, given the type of censorship you'd have to do.

• 17:38Speaker 01

  Yeah. It's like, I don't know. They've figured out how to censor other stuff. How racist is Claude? Not that racist. If you can figure out how to make a model not racist, you can figure out how to have it not say politically controversial things, which by the way are like 0.0001% of queries. People are asking what basketball shoes to buy, not, um, you know, what happened in their country in 1989, primarily. So, um, so, yeah, it's, it's been much, the, the sort of, the story of the Chinese government with respect to AI has been, um, more about how they, I think, have like, um, maybe learned some lessons from, uh, the heavy hand that they put on the semiconductor ecosystem.

• 18:19Speaker 01

  I mean, that was very rocky. At one point, they jailed everyone who was running the most important sort of industrial policy big funds. Uh, 2021, 2022 or something. Yeah. So, so they had like a hundred billion dollar fund and the top seven people have now been disappeared for corruption. Right? The reporting is that that was downstream of she being frustrated about the relative amount of progress that the indigitation, indigenization has been made. And like, look, if the VC firms are going to put up the money. You know, you can spend it on other things. So yeah, it'll like, there's, there's more downside than upside risk.

• 18:57Speaker 01

  I think for the like eye of Sauron to come on this and for whatever reason, it's, it's been pretty low touch for now.

• 19:05Speaker 00

  From published documents or anything else you can get a sense of like, how top of like, how worried is the administration about this?

• 19:10Speaker 01

  It's really funny. So, so the, the Chinese, uh, the Chinese system, I mean, really since Mao has done these things called like study, study sessions, where they literally like sit around, bring in the top experts and academics and like quote unquote, learn about a thing, you know, like have a lecture series, like ask questions. They had an AI one in May. We wrote it up. We'll link it in the show notes. You can kind of triangulate what exactly they're focused on by like which, which guests they bring in to, um, uh, to talk about them. You know, pretty anodyne people, not, not very crazy things. AI is important. We need to care about it. Not a ton of AI doomerism. I think there's like,

• 19:49Speaker 00

  Is there like a Chinese eleazar or like, you know, do they have the, that ecosystem?

• 19:52Speaker 01

  No, I mean, the thing, the thing about like the right lens to understand the Chinese, the Chinese government's approach is, you know, what is it going to do to national, national power and what is it going to do to political stability? And I think there is a sort of, um, a, a broad understanding that the sort of social dislocation that, um, this technology could potentially produce with job displacement is like an opportunity and a risk. And like, we'll see how it plays out. It's not hitting, um, you know, as hard as what, um, sort of reforms in the early nineties with state owned enterprises did, for instance.

• 20:32Speaker 01

  So I think they're relatively confident in their system's ability to kind of absorb that, um, uh, dislocation and that will come from the productivity growths. And on the like AI doomer safety side, not a lot, um, from the, from the government perspective. You know, a line here or there, uh, you see, um, uh, the sort of level of pilledness of various, uh, founders is interesting. One of the top AI people at Alibaba, he just talked about AGI for 30 minutes at their like big annual conference. It wasn't anything. Novel or interesting compared to what you would see in the like it's like very, very analogous to what you would see in the discourse in San Francisco.

• 21:15Speaker 01

  But it was remarkable that it happened from such an established player of like talking about, you know, grand vistas of like new scientific opportunity and whatnot. So there is a real interplay in the, in the discourse. I think much more from the sort of private sector founder perspective, you know, they all listen to Dwar Cash and Jacob's show.

• 21:36Speaker 00

  I do, I do have always there, someone will occasionally send me like a Chinese translation of one of our episodes and like, it does some real numbers. Like I'm shocked at how much people in China seem to follow along with like the discourse and like media here around AI in the US.

• 21:50Speaker 01

  And this is one of the like perennially frustrating things for me is in the other direction, like there's like 10 of us, really, whose job it is, is to like do the translation in the other direction and follow the Chinese AI ecosystem and explain it to the US. Whereas in China, like, oh, I'm glad, I'm glad that's happened, but like, yeah, there's entire media organizations that are following what's happening in Silicon Valley, like translating the interviews, writing lessons. And that just doesn't happen in the US for various structural reasons, which we can delve into or not. The looking glass is very much one, is one directional.

• 22:30Speaker 00

  Yeah. What's the general attitude, you know, of like Chinese founders and builders toward like, I mean, as they're consuming that content, is there this feeling of like a race or is there a feeling of like excitement and we're all collectively trying to build this technology? I'm sure it's not as simple as any of that.

• 22:44Speaker 01

  Look, I think the, the main focus is a kind of competitive pressure, one, to stay alive in this like incredibly hardcore, like technology and commercial competition, both in the big companies as well as in the small ones. Like, you know, it's been funny seeing this mirroring of like all the AI labs there are now working 996, like China's never stopped, right? And I think every time there is a big opportunity, the competition is just even more fierce. And there's less breathing room for these for these labs to survive. So that is probably comprises like 90% of the day to day worries.

• 23:27Speaker 01

  I think there is a broader sense, and you can read this in some of the DeepSeek founders interviews, that he does feel like he's on this like humanistic quest to like, you know, create a new technology and open like new vistas of of of of of science and and innovation, which is which is nice, but there's also this very frustrating backdrop, which I think is probably best exemplified by a Johnny Johnny anecdote. So he was the ByteDance, the ByteDance founder. His old social media posts from like the late 2000s, early 2010s make clear he's liberal, like he's frustrated with censorship and whatnot.

• 24:08Speaker 01

  And he was kind of running, you know, basically running a media company like he had a he had like a BuzzFeed equivalent of BuzzFeed like was big and good and tech enabled. As TikTok in China, Doyin was growing.

• 24:23Speaker 01

  He and his leadership team like disappeared for a few days. And then at like 5:12 in the morning on like a Monday, he posts a letter, which is basically an apology saying, we did a bad job of moderating our content. We need to like serve the party better. We're not upholding, you know, socialist values and this sucks. So there's this, there's this like really tragic like central tension is that the, you know, a lot of the leading lights of the Chinese technology ecosystem do have this global liberal perspective, oftentimes have worked worked in the West or in Western countries,

• 25:08Speaker 01

  aren't, you know, really all about like making the CCP great again. And, you know, have kind of like, you know, globalist in the nice cosmopolitan, let's say, visions of what what they produce can do, but they're living under a system and in a sort of like global state of things. Where it doesn't matter what they think. So, um, you know, as this technology becomes more and more relevant from a, from a national power perspective, it seems inevitable to me, you know, if, uh, sort of the Chinese government continues to be run in the way that she has run it for the past 15 years,

• 25:48Speaker 01

  that the sort of operating space for this type of, um, you know, positive sum interaction is gonna, is gonna shrink.

• 25:56Speaker 00

  It feels like there's a real financing gap today in the Chinese ecosystem. And in the US, you've got tons of venture investors, rich capital markets, folks like Nvidia that are, you know, would love to have as many potential model companies, that can exist. Um, and it seems like, you know, there's one version of the world where the Chinese government is just happy to let everyone club each other to death, see who the few winners are. Uh, obviously we've seen scaling laws kind of seem to continue to hold up. It feels like this is going to be a capital intensive game. Do you think that that is how it persists? Or is the Chinese government step in and try and solve this in some way?

• 26:24Speaker 01

  Okay, so let's do a bit of a like net assessment of, uh,

• 26:28Speaker 00

  Love a good net assessment.

• 26:29Speaker 01

  Yeah, you gotta do it. Of the, of the Chinese and,

• 26:31Speaker 00

  I'm sorry, I'm sorry to get you a whiteboard to, uh, to, to really do it.

• 26:34Speaker 01

  So, you know, what, what are the inputs to like have, uh, great models that you can deploy at scale? You need talent. China's got as much talent as any other country in the world. Um, you need energy. They probably have, uh, enough energy to, to run that as far as we're going to need to over the next few years. The real constraint is going to be compute. And, um, right now it seems like the Trump administration has decided to continue the Biden administration policies of not giving the Chinese government open, or the sort of the, the Chinese mainland like as much access to compute as they would want, um, in the interim. So then what we're having a sort of

• 27:14Speaker 01

  battle on is like whether the, uh, sort of Western finance plus, um, TSMC plus like the entire Western supply chain for semiconductor manufacturing equipment can, uh, will be able to sort of outscale with an enormous like a, a lead of probably 10x where Huawei is right now, maybe 15. The domestic Chinese ability to sort of copy, um, and, and scale up the same thing. And, You can look at the examples of electric vehicles and the solar industry as moderately difficult emerging technologies that China really has been able to scale up in a way

• 27:57Speaker 01

  that dwarfs the rest of the world. But I do think that semiconductors are different. We have basically had an open tab when it comes to the Chinese government, allowing their hardware ecosystem to spend as much as it takes to build it up. And they are where they are today. The Chinese government can spend a lot of money, but global capitalism can spend a whole lot more. I mean, the fact that Alibaba is worth like $200 billion and Nvidia is worth four trillion, five trillion, all the sort of like swing sources of capital seem to be coming America's way. So there isn't really like cavalry going to come in

• 28:37Speaker 01

  from a sort of like, like a technological defector of like, oh, is Japan going to switch sides? I don't really think so. Such that I do feel kind of confident that the money that the West is going to be able to, the money in technology the West is going to be able to deploy to scale up on the compute side is going to be able to swamp the Chinese players for a long time to come.

• 29:01Speaker 00

  And the next year, is there going to be like a greater or smaller difference between American and Chinese models?

• 29:07Speaker 01

  So the models themselves, who knows? But, you know, we've kind of learned this. It's not just the model, it's the ability to serve it, right? And that is really where you start to see these constraints. I mean, like, like if you think the rate limits on Claude and OpenAI are bad, like just try using a Chinese model, right? And so that both takes compute and it takes money. And look, maybe once the business model starts to click in, that starts to change. But as long as you do have this relatively substantive wall not allowing China to buy the best chips in the world from the place who makes 10

• 29:49Speaker 01

  times as many as what the Chinese competitor can make, then you've got a big edge.

• 29:56Speaker 01

  That, you know, doesn't necessarily mean that the gap between closed, you know, Western models and Chinese models is going to be all that big, but like in order to reap the sort of gains from a business perspective and from a broader like national productivity growth perspective, like you need to have.

• 30:14Speaker 00

  Like, how many tokens does each person get for?

• 30:16Speaker 01

  Exactly. And that's the thing that I think is domestically going to be constrained relative to the West and China for a long time to come.

• 30:23Speaker 00

  Yeah. Well, it's interesting, though. It sounds like the Chinese government is focusing on the exact right area, where it's that like, basically, you know, opening up capital markets more, putting more money to work without solving this hardware problem is not actually all that helpful. It's like, that's, that's the thing that, you know, needs to be figured out. You kind of alluded to, to some of the US government policy, you know, Trump administration continuing some of the stuff, but the Biden administration's done. Can you just give our listeners like a walkthrough of like USAI policy toward China over the last five, six years and kind of where we are today?

• 30:48Speaker 01

  We're starting 2015, 2016. So late Obama, you have this consensus start to shift in America from the more we engage with them, the more liberal and comfortable we'll be with China's rise in the world to this understanding that the direction that Xi is taking, the Chinese government, is not one that the US is going to be comfortable with anytime soon. So, starting late Obama, then in Trump won and into the Biden administration, you had this sense that China is a strategic competitor. The US just can't let them do whatever they want and gain in every fund that we consider to be of like national strategic

• 31:28Speaker 01

  importance. So there are places that we're going to have to start controlling. So, and towards the end of the Trump administration, there was a big focus on telecommunications and Huawei. And when the Biden team came in, thankfully, there were a handful of like pretty pilled folks in the White House in 2021 and 2022 that saw just how important compute was going to be to this sort of new paradigm of competition. So, September 2022.

• 31:58Speaker 00

  Who were these people? Because I feel like before ChatGPT, it was not like, you know, I wouldn't, I wouldn't expect that so many people in the administration to know that.

• 32:03Speaker 01

  Yeah. I mean, it was, it was a really interesting. Interesting happenstance. So there are a handful of folks at CSET, Jason Matheny, Ben Buchanan, Chris McGuire, Safe Con, you should have all these guys on, great for your show. You know, had been writing about AI for years and

• 32:21Speaker 00

  They were reading all the research.

• 32:22Speaker 01

  They're reading the papers and they're just like, all right, this could be a big one. So in October 2022, you have

• 32:28Speaker 00

  A month before ChatGPT.

• 32:29Speaker 01

  A month before ChatGPT, you have this very dramatic move to start to control both exports of AI chips as well as semiconductor manufacturing equipment. And then a month later, we have ChatGPT and everyone's like, oh, like, like, at first we're like, oh, this is kind of weird, kind of interesting. And they're like, oh, okay. Like, I get it. Scaling laws. Like, here's what we're trying to stop. So there has been a sort of, there was a dance over the course of the Biden administration where on the one hand, Nvidia wants to sell chips. So they make something that's like right under the limit. And then the government is like, ah, no, that's not cool. The parameters of which manufacturing equipment also got twisted over time. And then they wanted to make sure that the,

• 33:11Speaker 01

  the Dutch and the, and the Japanese did it at the same time. So it was kind of delayed. And then you had this big scandal of TSMC basically selling a ton of wafers to a Huawei cutout that then they ended up getting smacked for. So there was this understanding that like, look, we want to win on compute. And one of the ways we're going to win on compute is by some throwing some gears in the sand of the Chinese computer ecosystem and not letting them just like buy up everything. And, you know, not great, you know, not perfect, not terrible, but like on the margin, definitely slowed down the development of the Chinese semiconductor and, and broader AI ecosystem. So in comes the Trump administration, the first few months, you had a team that seemed to be very aligned with this view

• 33:53Speaker 01

  that controls were important. Enter David Sacks, exit the China Hawks, thanks to Laura Lumer. And in comes Jensen Huang into, into Trump's life. And we've had this real head spinning drama of will he or won't he allow best American chips to sell to China?

• 34:13Speaker 01

  An interesting wrinkle in this is that the H20s, which are good, not great chip, you know, like one generation behind, kind of limited in some ways, but still very powerful. The Trump administration decided to sell into China only for the Chinese government to say, screw you guys, we don't, we don't want your stinking chips. Now, why that happened was a fascinating, is like, is a big puzzle that the community is still very much debating. On the one hand, maybe Xi has bad information and the Huawei lobbyists got in and told them that we've got better chips and more chips than you really think we do.

• 34:51Speaker 01

  Maybe it's a negotiating ploy to get Blackwells, you know, instead of this like gimpy knockoff model. And then there was this big drama in the lead up to Trump's summit with Xi in Seoul, where he got on the plane, the stock went up 10% out of the expectation that he was going to decide to sell them. And Lutnik and Rubio and Besse and Davidson Greer are like all huddled in Air Force One being like, Trump, don't do this. And he comes off the plane, he doesn't, he doesn't sell the chips. But now we have another story that they're considering selling a, you know, a version of it. So this administration, I think, is very, is definitely of two minds of, on the one hand, this is an edge that we want to keep.

• 35:36Speaker 01

  On the other hand, maybe there are some upsides to keeping China buying Nvidia chips for a while.

• 35:41Speaker 00

  Yeah, I get the argument for not selling them. How would he strum in the argument for selling them?

• 35:45Speaker 01

  So the most compelling case that Jensen has is that AI accelerators are not just their hardware, they're the software as well. And the software keeps getting better, partially because, you know, Nvidia and AMD and Huawei themselves invest in their own architectures and also because there is this broader kind of global community of developers, which is Which is contributing to the ability for CUDA to just like be better than a random chip you get off the shelf that doesn't have the software optimizations. And you know, there are thousands of very, very good Chinese engineers who wouldn't, you know, who, given their druthers, would love to stay on Nvidia because they are the best chips. And by not

• 36:27Speaker 01

  selling chips into, these Nvidia chips into China, there is a risk that that engineering energy instead gets spent on improving the sort of Huawei software ecosystem.

• 36:40Speaker 00

  I feel like people have also written about this like ideal Goldilocks scenario where like you give, you know, Chinese companies enough of chips that like they don't spend too much time like building their own. Like I feel like Ben Thompson's written about that and Dylan from Semi Analysis. Is there like a way to stick the landing where it's like you still have most of the, of like the cutting edge chips in the US, but like you've given at least enough of an incentive not to like go all in on Huawei and the local ecosystem?

• 37:04Speaker 01

  Howard Lutnick said, you know, we want to get them addicted to American chips. And I think this is a story that has played out so many times over the past 30 years that the sort of, the goal is indigenization and it's going to come whether you like it or not, whatever your business plan, whatever your China strategy is, if this is, if, if what you're selling is an important, is like a nationally important strategic research, resource, then you are going to have domestic energy, which has been supercharged by the fact that there have been so many export controls and it had, there have been choke, these choke points that have been raised. People say like, oh, like Huawei went from this like second source, no one really wants to deal with to like what's front and center.

• 37:48Speaker 01

  Well, you know, the next administration is only three years away. I don't think these companies are stupid. And you, I would almost make an argument to the other side where if you're trying to make a, build a lead, you know, why give them this bridge and this breathing space that selling a lot of chips would provide because the sort of, as we talked about before on the hardware ecosystems, like the hardware, the Chinese hardware ecosystem is not capital constrained, right? They have all the energy, they have all the attention. They've had more money poured into it than any, you know, it is the biggest industrial industrial policy project in human history. There's been more money poured into it than than anything ever. So they're

• 38:29Speaker 01

  going to try as hard as they can. And and my my takeaway is that selling Nvidia chips, particularly into China, not even allowing Chinese firms to rent them in Malaysia or Singapore or AWS or what have you, the drawbacks don't exceed the benefits. But look, these are these like, there are a number of unknowns which are in this. This is a very complex sort of equation to pan out. Like, it depends on your assumptions of of how good Huawei is going to get. It depends on your assumptions of to what extent, you know, Nvidia is capital constrained. Like, are there, you know, is the is the limiting, is what's limiting American or sort of Western AI build out compute? Is it energy? You know,

• 39:14Speaker 01

  like, is there more? Would more demand for TSMC actually like me lead them to make more chips? Or are they already kind of tapped out? So I don't know, a lot of variables. It's a complicated thing. The one illustrative point I would make to you is that I have tried, you know, I've done a lot of shows on my podcast about this. I have tried to find an expert that has not that isn't sort of financially tied to the to the like Nvidia upside outcome of making the case. And I haven't been able to find that person. So there seems to be a pretty strong consensus among the folks who take this seriously that

• 39:56Speaker 01

  the balance leans towards not selling them the chips and definitely not selling them the semiconductor export equipment. But there are legitimate arguments on the other side.

• 40:04Speaker 00

  What is like the status quo today of this ban? Like, is it is it effective? I feel like the Wall Street Journal had some piece about chips getting smuggled in, you know, recently. It feels like you can, you know, rent some of these chips in clouds, maybe in other countries, you know, on the ground for these Chinese firms. Like, are they pretty constrained in their access?

• 40:19Speaker 01

  Yeah, I mean, that's the that's the sort of interesting thing about this is there's nothing stopping Chinese firms from renting compute abroad. And renting the best chips abroad. That whole lock-in thing I was talking about is like, these companies are still training their models on Nvidia. They're just doing it like in Malaysia or with the chips they already have or the chips that they've already smuggled. Because Nvidia is still a lot better than than what Huawei has to offer. So the upside of like actually legally selling the chips into China, you know, really is just like, I don't know. A couple, you know, maybe 10, 20, 50 billion dollars more of revenue over a five-year horizon. But it's unclear to me how much of that money will be marginal money versus money that the Chinese firms are just spending.

• 41:05Speaker 00

  I thought the Biden diffusion rule had something around like, you know.

• 41:09Speaker 01

  Oh, yeah. So that's gone.

• 41:10Speaker 00

  Okay, so that's completely.

• 41:10Speaker 01

  Yeah, yeah, yeah. We're not, we're not too, well, it's interesting because.

• 41:13Speaker 00

  They were trying to prevent this, right?

• 41:14Speaker 01

  It's, yeah, because this is, this is what they were trying to do. I think the Trump administration is less bullish on it, but there's this very weird liminal thing where they like issued a rescission. They said in an FAQ from BIS that the diffusion rule doesn't exist, but they haven't actually crossed it out on paper. Presumably because there is, there is still like an internal fight in the Trump administration of whether or not this diffusion rule is a thing that we're going to live by or not. So, yeah, it's, you're asking the right question. A lot of this stuff is TBD. And the thing about the Trump, the Trump administration, they just change their mind all the time. Like, we're optimizing for vibes, we're optimizing for headlines.

• 41:53Speaker 01

  The folks who try to project some grand strategic thinking on it, I think are connecting dots that that don't actually exist. Like, we're like, he's all about sort of internal power struggles and, you know, being this like flexible player or something. So I would be shocked if we ended up, you know, given how many twists and turns we had over the past year or, you know, 10 years of Trump, that we'd end up getting real consistency on this thing beyond him saying, okay, AI is important. We want to like win and.

• 42:24Speaker 00

  So today, these Chinese firms can access decent amount of compute abroad to train. They presumably, if they had popular products, could run inference on those products abroad. Like, I can't tell how much of a constraint it actually is.

• 42:34Speaker 01

  Yeah, I mean, there's some kind of like data privacy law stuff with like using cloud that's outside China and into China. So that, I think, is one of actually more of the constraint on the Chinese side as opposed to the American. But yeah, I mean, it's a it's a it's an access to capital compute problem as much as it is a like the US government isn't letting them have access to Nvidia today.

• 42:58Speaker 00

  On the Huawei side, like, obviously, there's like technological improvements that need to happen. And then there's also just like being able to manufacture at scale, right? And have any sort of like demand for it. I realize this is probably a hard question, but like, do they have a shot? Like, I mean, how do you think about that question when you talk to other folks?

• 43:13Speaker 01

  Yeah, you know, if you go back to 2020 and 2021, the the chips that Huawei were designing and making at SMIC were basically as good as Nvidia's chips. So from a design perspective, they are not lacking in any sense of the word. So it really comes down to the sort of scaling within the Huawei fabs and within the SMIC fabs. And the big constraint that they're operating under is they don't have EUV. So that means that their chips are sort of stuck at 7 nanometer and you know, you can push it. But like, all the technological trees they are going down are the one are ones that all the Western

• 43:58Speaker 01

  fabs and the broader global ecosystem decided were less efficient because using EUV lithography to make this stuff was a better, you know, mix of like effort and yields and like just capital and technological research allocation. So a lot, you know, one of the one of the big ironies of the Biden administration semiconductor equipment control policy is that semi cap basically doubled in 2020 from 2022 to 2023, once they controlled this because there was this big influx of capital. Folks, you know, the Chinese semi cap, the Chinese semi ecosystem sort of saw the writing

• 44:39Speaker 01

  on the wall and they're like, oh, we got to hoard both chips as well as manufacturing equipment. There are also still a lot of loopholes where like there's, you can have a subsidiary which is 45% owned. There are some fabs where like one side, like a fab on one side of the street is controlled and the fab on the other side of the street isn't. And there was a big lag in sort of when the controls came on in the US versus in the Netherlands and in, and in Japan. So they do have a lot of equipment in the, in the building. But again, what we're focused on is like the relative amount of compute that Huawei is going to be able to manufacture versus the rest of the world. And the fact

• 45:23Speaker 01

  is like, if you look at the Huawei roadmap versus the Nvidia roadmap and the, and the TSMC roadmap, like, you know, I will, I will send you the like infographic I've vibe coded. But it's basically like a 15, it's like a 15 to one ratio at least for the next three years. There are some, there are some knobs.

• 45:45Speaker 00

  Ratio of production or?

• 45:46Speaker 01

  Oh, yeah. The compute that is going to be made. And, you know, there are some knobs that sort of change that from 15 to 13 to 10. If you kind of make different assumptions about Chinese access to high bandwidth memory, or maybe Huawei gets better at designing, this, that and the other thing. But like, at least for the next three years. I mean, 10 years from now, 20 years from now TBD, but in the, in the near to moderate horizon, like this is a real edge that the Western ecosystem is going to have compared to China's.

• 46:20Speaker 00

  Yeah. And I'm struck by, it's talking about lithography, like should, are we not paying enough attention sucking up to Netherlands?

• 46:25Speaker 01

  Well, you know, this is the interesting thing is that because there is an enormous amount of American technology in all of these machines. I mean, you know, ASML like was American, you know, there are lots of lens, like there are lots of parts which are like fully. Supplied by the US and like so, so I had Jake Sullivan on my podcast a few weeks ago. And the, the main sort of hypothetical I got him to engage with was whether or not the US should have done it the hard way as opposed to the nice way and basically saying, sort of doing a, doing a fait accompli with these, with these allies countries selling equipment,

• 47:08Speaker 01

  saying, sorry, you can't sell anything. Because what, because what ended up happening was the Chinese, even though the Chinese, Chinese firms were not allowed to buy UV equipment, they spent tens of billions of dollars buying DUV. And that's really what's powering all of this, all of this Huawei build out, as well as the legacy, the legacy chip build out. So, there's like a lot of latent power that still exists. Like, they can't really say fuck you on this. We, we do hold the cards here, but the Biden administration decided to, to value the alliances a little more, which led to all of this kind of like frustrating, two step forward, one step back.

• 47:50Speaker 01

  You know, there was a hope within this community that the Trump administration would put the pedal to the metal on this. And it's like, look, if the Netherlands is worried about America leaving NATO, how worried are, you know, what's, what's one company's like political economy really matter in the grand scheme of things? Same with, same with the Japanese firms. But that has not, that's not how it's really played out. And because of the whole rare earths,

• 48:16Speaker 01

  drama between the US and China, it seems like whatever controls that the Trump administration was considering to tighten on the semiconductor manufacturing equipment side are, are on ice for now.

• 48:27Speaker 00

  Yeah. Interesting. I guess if you had the year of the, you know, Trump administration, and you could kind of like, you know, wave a wand and put one policy forward, like anything, you know, that you'd be doing?

• 48:36Speaker 01

  So on the export control side, I would say,

• 48:41Speaker 01

  You know, I want to take it in a slightly different direction. So the Chips and Science Act, which was passed in 2022, led to, you know, part of the reason why there's been this whole kind of domestic fab renaissance. I had two parts to it. So one is the is the kind of loans, grants, tax benefit to R and D tax benefit that has helped build all these fabs in Arizona and Texas. And but there's also this R and D component.

• 49:13Speaker 01

  It was $13 billion to sort of re to kind of create like do basic and translational research that would push the frontier of semiconductor manufacturing forward. The Biden administration kind of fumbled the bag on this. They were sort of slow to start spending the money. They didn't end up developing a lot of friends, friends with an industry. And the Trump administration a few months ago canceled it or canceled the iteration of the nonprofit that was going to run this that the Biden administration had set up. Now, what's going to happen to that money is TBD. I mean, whether it goes into like just buying stakes in companies because we think

• 49:56Speaker 01

  that's cool now, whether they try to spin up another version of of this, whether it just like ends up being a kind of subsidy to corporate R and D is an open question. But like, it would be a bummer if the biggest kind of injection of research and development, which if we're looking at like a 10, 20 year horizon, is what is going to matter when it comes to this sort of like semiconductor and broader compute competition. Like, I would like that chunks of money to do chunks of money at that scale to do basic research do not come around very long, you know, very, very often in the American political system. And I and I do have hopes that the Trump administration will still come up with some

• 50:40Speaker 01

  creative and impactful ideas to spend that money.

• 50:42Speaker 00

  I'm sure this is not your favorite part of being a China expert, but I imagine I'm contractually obligated to ask you a little bit about Taiwan.

• 50:48Speaker 01

  Sure. Let's do it. Only for you, Jacob.

• 50:51Speaker 00

  Yeah, people often war game a Taiwan blockade, Taiwan invasion, like, you know, how likely is this in the next decade?

• 50:59Speaker 01

  All right, so let's start with the Trump administration and then we'll do like a 10 year thing. So the American policy towards Taiwan, to defending Taiwan has been this idea of strategic ambiguity that like, we're not going to commit to Taiwan that we're going to defend them so they don't, you know, try to re-invade mainland China, which is something Chiang Ha-sek was considering a number of times. And we're not going to tell China what we're going to do to sort of, you know, make it clear on one side or the other. The Biden administration and Biden himself said a number of times, yeah, we defend Taiwan, basically, and sort of like ad-libbed. And the Trump administration, there were a number of people, you know, there

• 51:39Speaker 01

  is a big debate, I think, in that broader, like, right wing ferment of to what extent this island is a place that matters for us. I mean, we had Elders Colby writing a whole book, basically saying, America should care about nothing else in the world but Taiwan because it is so important. They make all the chips. You know, this is our way to contain China, what have you. And, you know, we have other strains that couldn't give two shits. It's halfway across the world, 20 million people, like, let's focus on killing, you know, on overthrowing Maduro and like shutting down drug runners. Why are we worried about this country halfway across the world? So, you know, we talked earlier about this worry

• 52:23Speaker 01

  in the lead up to the South Korea summit that Trump was going to kind of just like fold on AI chip exports to China. There was another big concern that he was going to fold on Taiwan. And you even had articles written from folks in the White House leaking how concerned they were that he would give something big away. Now, look, it's a similar dynamic to Ukraine, where like, just because America says, we don't want you to fight anymore, doesn't mean that the Taiwanese people have no agency in this. But, you know, a big

• 53:04Speaker 01

  Like it is a big part of the sort of the balance of the past 75 years, which has kept Taiwan free and independent, has been this this commitment from the US and from other countries that, you know, it would come, it would come to, it would come to Taiwan's defense. So we're seeing a big kerfuffle now. The the new Japanese prime minister said the quiet part moderately more out loud than past Japanese prime ministers said. And like, like now China banned sushi, now China banned like, you know, seafood, seafood imports from from Japan. So this is, this is still a very hot topic. I think he kind of gets it that this would not be great for the US. Like, the package that you would

• 53:49Speaker 01

  need to receive for China in order to sell Taiwan, you know, sell Taiwan up a creek is like, I don't even know what would be on the side of that ledger to make it exciting and acceptable for like, the American polity or even a president. But that is, I think, a big concern. Another, another interesting risk factor is Taiwanese domestic politics and how that drives thinking in Beijing. So we've had two DPP presidencies. This is so you two major parties, DPP and KMT. KMT, ironically, this is Shanghai Shaq's party.

• 54:31Speaker 01

  You know, the Taiwanese, the Taiwanese nationalists. But they have now, you know, some like horseshoe theory thing. They're the ones who are much more friendly with Beijing and more open to like, rapporteze. DPP, more left wing, and more kind of like, not pro-independence, but less comfortable with like, bringing more integration between the mainland and Taiwan. So the, the concern, like, the, the risk factor is that she gets impatient, and doesn't necess, and sort of sees the writing on the wall from an age perspective for him, wants to like, end it, and also sort of sees to

• 55:14Speaker 01

  Trend lines in Taiwan going in a way where it seems less and less likely that you would have a, you know, more political integration between the island and, um, uh, and the mainland. And we're gonna, you know, we've had a relative resurgence in KMT and like the better the KMT does, the less stressed out people are that Beijing is going to overreact and they're going to want to play like the nicer long game than the sharper short game when it comes to a blockade or what have you. But, um, so anyways, everyone should care more about domestic Taiwanese politics. It's probably the most important variable when understanding, um, uh, when understanding these

• 55:54Speaker 01

  dynamics. But, um, at the end of the day, um, my take is that Xi himself is not the type of guy that just goes willy nilly invading places. Like, he has been in power for over a decade now, and I think that is enough, uh, you know, those are enough dated points to show or reveal preference. And for all of the sort of obnoxiousness that we've seen, um, with the Philippines and the Scarborough Shoals, that weird kind of like battle, like hand to hand battle in the Himalayas between, uh, uh, China and India over COVID, um, you know, the increasing like encroachments of Chinese fighter

• 56:33Speaker 01

  jets kind of like going, dancing in and out of the, uh, of Taiwanese airspace. Like, this is not what you saw from Putin before he invaded Ukraine. Before he invaded Ukraine, he like invaded Georgia, he like invaded Syria, he invaded Ukraine once, um, uh, and kind of got comfortable with the, with like very dramatic use of military force. So, um, a world where China doesn't like the results of a domestic Taiwanese election and starts to, you know, flirt with or even do something that looks like a blockade is, you know, non-zero. I would put in the single digits if we're looking at a

• 57:14Speaker 01

  five, you know, over a five-year span. But they're not stupid and they understand the downside risks to doing something like this, um, which could be really, really severe for the, um, uh, for the Chinese economy and even potentially for, for, for stability, the stability of the party. So, um, the risk reward matrix doesn't make a lot of sense. It didn't make a lot of sense for Putin in February of 2022. So, um, you know, like,

• 57:42Speaker 01

  We'll have to see. This is not the thing that that's keeping me up at night, though.

• 57:45Speaker 00

  Yeah, as you're particularly AGI pilled, it feels like, oh, it's all TSMC and that's like the the big thing. But it turns out there's many factors at play here.

• 57:52Speaker 01

  You know, this is the Ben Thompson argument that like if America gets too far ahead, then they'll want to bomb the fabs or bomb the data centers or something. And like, maybe, but hope springs eternal. I think there's, at the end of the day, like, the US and China are each going to make up roughly a quarter of the world's GDP over the over the next 10, 20, 30 years, regardless of demographics, regardless of whether or not China hits a financial crisis. And that is sort of a fact. You know, maybe if we live in a real sci fi world where where AI means that America grows at 10% and China doesn't get it and they're growing at 1%,

• 58:35Speaker 01

  we can have another conversation about whether that means they're going to feel like squeezed like Japan felt in, you know, summer and fall of 1941, but that seems a little far fetched.

• 58:45Speaker 00

  Yeah. Is there anything else that's happening either in the Chinese AI ecosystem or China at large that you feel like is really under discussed in the media today?

• 58:53Speaker 01

  You know, folks are starting to get a sense of the robotics ecosystem. I think it's

• 58:59Speaker 01

  it's going to be a real challenge for the West to scale up manufacturing on that. I mean, we've been able to scale up manufacturing of chips. We've been able to do a really remarkable data center build out even faster than what China has been able to do on that front. But that's different than just like giant manufacturing. And this is a playbook that China, you know, has run a number of times with with drones, with electric vehicles. And insofar as manufacturing robots at scale cheaply is something that is going to unlock a lot of the 20, the 21st century, then yeah, this is something that the Chinese,

• 59:41Speaker 01

  the the sort of broader Chinese ecosystem may end up having a real, a real engine.

• 59:45Speaker 00

  Totally. And one thing I'm struck by is so much of robotics is, you know, about data collection. And it seems like a lot of the stuff is actually already being deployed around China, which like gives you a huge advantage to start gathering data. I think everyone in the US is trying to figure out like the right way to start getting these things out there.

• 59:58Speaker 01

  I remember hearing this story for for LLMs too, right? I mean, like, okay, like. Skill's gone, like we have Merck or that's like doing its thing, right? But it's been an interesting, like the, the, the sort of relative weight of compute versus data versus talent in the sort of like AI, LLM ecosystem, I think has sort of ebbed and flowed over time.

• 1:00:25Speaker 00

  Totally.

• 1:00:25Speaker 01

  And, you know, this is what we were saying with China. This, this is like in all the like pre chat GPT books, everyone's saying, oh, China has so much more data than the West, like they have all these CCTV cameras, like they have these closed ecosystems, like of course they're going to win. So I think it's, I think the sort of, the, the, the factors of what is going to really turn robots on is still an open question. And, um, you know, the, the relative strength of the US is still models when it comes to the, the robotics perspective. Now, like having models and having compute means you get to like, on the LLM side means you get to reap all the benefits. But like, you need a lot of robots in order to like use those models and use them at

• 1:01:08Speaker 01

  scale in a way that is, is like financially renumeration for the folks manufacturing them. And if you're sort of dependent on Chinese robots, then TBD. I mean, you know, there's an interesting question of like, is that a comfortable steady state for the West to have a lot of Chinese robots running around America?

• 1:01:29Speaker 00

  I think Chinese people have watched iRobot to, to be cool with that.

• 1:01:32Speaker 01

  Yeah, I mean, we, I remember, I remember Jacob Helberg, who's now at the, um, uh, State Department, like tweeting Chinese humanoid robots, like we have to ban them in all caps, like three or four years ago. So yeah, iRobot's like a thing that now policymakers are now currently indexing on. So you're onto something, Jacob.

• 1:01:49Speaker 00

  Well, no, I feel like the argument that people like to make that the West has a chance is, you know, well, all these jobs are so much more expensive in the West. Like actually from a business model perspective, how much, how much are you really going to gain deploying these robots like within China relative to what you gain deploying them in the US? And so the economic prize may end up being so much larger here that. You know, enough of an incentive to overcome some of the manufacturing disparities. Jordan, it's been a fascinating conversation. I always like to end our interviews with some quickfire questions where we stuff some overly broad things into the end. And so maybe to start, if you could clone yourself and have your clone go to spend a ton of time digging into other areas, what are some like unexplored topics that you're super excited about?

• 1:02:26Speaker 01

  Dude, Medicare policy. Whatever. I thought we were going on the other.

• 1:02:28Speaker 00

  You want to come on the healthcare podcast?

• 1:02:29Speaker 01

  I thought we were on a healthcare podcast.

• 1:02:30Speaker 00

  All right. I would love to have, I would love to have your clone on my healthcare podcast.

• 1:02:34Speaker 01

  Um, that's a really good question. I think there are. So something I have been spending time on is thinking more about military applications of AI and the sort of fact is that like the, like what can be certain is that the sort of armies are not going to, or just militaries and national security establishments more broadly are not going to be like perfectly fit for the technological moment whenever the next big war comes. And sort of if you just, if you just look at the amount of change that you've seen from

• 1:03:15Speaker 01

  the way like battles are fought in Ukraine from 2022 to today, you've had radically different sort of like configurations and relative importance of different weapon systems and what humans are doing and what drones are doing. And that's not because we've had like incredible technological breakthroughs over the past three years. It's just that sort of from a doctrinal perspective, from a manufacturing and scaling perspective, from a command and control and perspective, there's this enormous amount of technological overhang that, you know, organizations, both, you know, military as well as like enterprise are going to have to explore in order to like really make the most of what's out there.

• 1:03:59Speaker 01

  And, you know, from a, from an enterprise perspective, like you have that creative destruction happening constantly all the time.

• 1:04:07Speaker 00

  Right.

• 1:04:08Speaker 01

  Right? So you reach the frontier of what's possible much quicker and without as much death. But that's not the case with. With militaries that really sort of like play in the dark for a while and all of a sudden like the lights are turned on and you're running around being like, oh my God, okay, like now we're now we have 10 times more people than we had a week ago. You know, we have all this energy, this talent, we have all this money. And we have this competitive pressure of like us screwing up and people dying because of it. And that drives an enormous amount of change and churn and innovation, both at the technological as well as the organizational level. So I've been really enjoying kind of reading the

• 1:04:54Speaker 01

  the case histories of this because this has happened a lot of other times in history where all of a sudden, 1914, like the machine gun, which had been around for 50 years, like was not relevant at the scale that it was. You know, in the Western Front in World War I and you had lots of different organizations all trying to adapt and train their people and do procurement and like, you know, have all these sort of counter reactions to this like incredible dance that incredible like death dance of innovation that the sort of two opposing forces of opposing armies had done. So exploring that, you know, it feels today like we're in this moment

• 1:05:35Speaker 01

  that's never been, never happened before because none of us have lived through one of this, of these like, you know, changes not seen in a century from a technological perspective that are going to, you know, ripple through both corporate, commercial, societal, as well as military cases. But going back and, you know, living in that like 1940, 14 moment, that 1941 moment, even this sort of like Gulf War, kind of like precision revolution moment has been a fun intellectual exercise. I have a book I will pitch to your audience.

• 1:06:09Speaker 00

  Please do.

• 1:06:09Speaker 01

  It's called The Social History of the Machine Gun. It's 200 pages long, written by John Ellis, who is this like recluse who like refused to come on my podcast. He apparently hasn't talked to anyone in like 30 years or something. That'd be a big get if you go. I know. I asked like four people and they're just like, Jordan, it's not you. It's him. He's just very cantankerous. Um, but uh, he, um, you know, he wrote sort of the story of the machine gun very concisely from a lot of different layers. So from this sort of like technological advancement layer of like how you actually came up with this and manufactured it and manufactured it to scale, the acquisition layer of how these, you know, who was trying to sell it, how the buyers were thinking about it, how that changed

• 1:06:53Speaker 01

  over time, the sort of tactical layer of like people having this big thing and like figuring out how to position it. And then the sort of broader organizational layer of the militaries of what they're going to do with this technology and like how it's going to end up like changing like battle plans and ultimately grand strategy. Um, and uh, you know, it's an incredible case study because like you'd think they would have gotten it faster. Yeah. But there is just so much like institutional, um, crud. And by the way, it was not obvious. Like there were people who were right, but the people who were wrong, like weren't total idiots and you could tell a story on the other side of it. And, and it's a very, the

• 1:07:36Speaker 01

  book is great. It's just like this very efficient way to sort of put yourself in the world in which this like giant, um, kind of revolution was going to come, um, and you know, take away like tens, even like hundred thousand, hundreds of thousands of lives, but the world couldn't see it. And you know, TBD on like what that is going to be for robots, for AI, for drones, what have you. Um, but uh, it's, it's always good to be reminded that like this is not a unique thing that has ever happened in human history. Like we've, we've hit, we've hit like technology shock many times in the past.

• 1:08:10Speaker 00

  I thought the Spanish Civil War was a famous example, right? Of everyone looking around, seeing what was happening there and then adapting those.

• 1:08:15Speaker 01

  Yeah, looking up, oh bombers, like, oh, okay, got to deal with that. Yeah, so, you know, there's a, there's a great example of like, uh, American generals watching the Crimean War in the 1850s. And then the Civil War breaks out and the ones who had, who had been in Crimea were like, got closer to realizing that they couldn't all line up like it was 18, you know, uh, you know, 1807 and Napoleon and we needed to sort of like spread out because the rifles had gotten that much better. So you can get glimpses into the future, but not all the lessons are applicable. And it's just this incredibly difficult, like naughty thing, which is impossible, but

• 1:08:58Speaker 01

  there are some kind of principles, which I think you can take out of it of just how confident you're going to be, what is noise, what is signal, like, and how you sort of build to make sure you're resilient into different potential futures that could play out.

• 1:09:12Speaker 00

  I feel like China is one of those topics that like intimidates a lot of people. And so I guess beyond, you know, subscribing to China Talk and listening to your podcasts, like any other places you'd point our listeners of like, you know, hey, I want to just keep relative tabs on what's going on, like best ways to do that?

• 1:09:26Speaker 01

  I would say go, um, you know, it's not COVID anymore. You can travel. I think you can over index on spending two weeks there, but I'd rather people over index than like not index at all and just kind of have it be, um, you know, New York Times articles or what have you, which has its own sort of biases. Play with Chinese models. They're all out there. They're free. I think there are some things that they're actually better at. So Kimmy is my favorite model for writing in English. I think it, it does my, um, my lyric generation better than, than Claude or Gemini or, uh, or Anthropic, which I, which I find really cool. TV is not great. There are some movies which are acceptable.

• 1:10:08Speaker 01

  I would Google like, uh, you know, what you can do is you can ask ChatGPT for the, uh, for the, the highest rated, uh, films on Do Ban of the year. This is like China's, uh, kind of like, it's a like user generated metacritic. It's like if Goodreads was actually, oh no, it's like, uh, like, it's like Letterboxd. It's like China's Letterboxd, sort of. Those are sort of fascinating, like little windows into, into modern Chinese society. I mean, they're like, like. They like, there are sort of constraints on what is acceptable content, but even sort of watching enough movies to start to see those like seams that the directors and actors have to live into is an interesting exercise.

• 1:10:46Speaker 00

  Do you buy like the whole thesis of that book?

• 1:10:50Speaker 01

  More or less.

• 1:10:51Speaker 00

  Engineering society, lawyer society.

• 1:10:52Speaker 01

  I mean, I think, look, it's like, uh, you know, there's generalizations there, but I think it's broadly correct. I mean, the, the issue with the, with engineering, the, the issue with characterizing China as a, as an engineering society is I do think there is like still a big ideological component and like a Leninist heart that maybe was on its way in pre Xi, but is now very much in full force and, and having to grapple with the sort of, uh, you know, ideological superstructure in which the engineers can play and optimize in is an important part of understanding, um, uh, the Chinese government and what it wants and, and the direction it wants, it wants to take, um, its country.

• 1:11:37Speaker 01

  I was talking to Dan Wong earlier about like what the good China books are or like, or like what entry level China books I would, I would, I would recommend to people. And there hasn't really been one in 10 years until he's brought it. So, um, you know, plenty of like really interesting kind of deeper histories, A Search For Modern China by Jonathan Spence. I think Joseph Torigian's biography of Xi's dad, um, is a fascinating, uh, kind of look into like what, what like being in elite politics in China really feels like or felt like over the course of the 20th century and like lives on through his son who is now running it. Um, uh, but yeah, sorry, sorry, break Nick.

• 1:12:15Speaker 00

  Amazing. Well, uh, I want to make sure to leave last word to you. Uh, where can folks go to learn more about you? China Talk, the mic is yours, anywhere you'd like to send them.

• 1:12:22Speaker 01

  I don't know, man. Uh, China Talk dot media, we got a podcast.

• 1:12:26Speaker 00

  Who is China Talk dot com?

• 1:12:28Speaker 01

  I don't fucking know. It's really annoying. To find Chinese TV that's right for you, what you should do is tell ChatGPT your favorite three Western shows and be like, what is a Chinese? What are some Chinese ones that are adjacent to it? And most of the, most of Chinese television is just put on YouTube. Um, and there are subtitles for like two thirds of the shows. So I would start there. Just like watch some domestic Chinese TV. Love that. Well, Jordan, thanks so much for coming on. It's a ton of fun. Bye, Chris.